Assessing Social Capital Indicators in Public Spaces in Central streets of the City of Sanandaj, Iran
Bibliographic record
Abstract
The social capital concept has been proposed alongside other capitals such as human capital, financial capital and economic capital. The aim of this research was to evaluate the social capital in streets, which are among the most dynamic urban public spaces. They provide physical connections for social interactions and consequently can enhance social capital. To this aim, four central crossroads of the city of Sanandaj, Iran were selected as a case study. This study is a descriptive analysis conducted by questioning 400 participants. The collected data were analyzed by using the SPSS (Statistical Package for the Social Sciences) software at the inferential and statistical levels. The findings showed that effective elements of streets to improve social capital include the promotion of environmental qualities and mixed land use related to social trust, the feeling of belonging, identity and place related to social norms, face-to-face relationships, and social participation related to social networks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".